Skyler Xie

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Skyler Xie

Position

Enrichment Student

Cohort year

2023

Partner Institution

Imperial College London

Links

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Research areas

Data science for science and humanities Management science Research methods Time series Modelling (Statistical methods & theory) Non-parametric & semi-parametric methods High dimensional inference Causality Artificial intelligence Applications (Machine learning)

Bio

Skyler is a doctoral researcher in quantitative economics at The Alan Turing Institute and currently holds a visiting PhD position at Imperial College London. Skyler is also trained at the University of Warwick. Skyler’s research combines economic theory with econometrics and data science to study economic incentives, resource allocation efficiency, and economic growth and volatility.

Since 2022, Skyler has been a member of the Data Study Group at The Alan Turing Institute, collaborating with public sector organisations (e.g., Department for Transport), listed companies (e.g., Johnson Matthey), and the financial services sector (e.g., Mastercard) to develop quantitative strategies and apply novel machine learning methods to investigate empirical challenges. Outside of work, Skyler is a tennis player.

Research interests

Skyler is interested in modelling dynamic changes and time series forecasting, causal inference, and complex networks with longitudinal data, especially for modern macroeconomic data with high-dimensional observations.

At the Turing, Skyler's research is focused within the Economics Data Science group and the Finance and Economics programme. He has been developing models of ranking as dynamic systems to optimise productivity and performance at both individual and collective levels. Recently, he has focused on integrating network science with econometrics to model economic shocks and volatilities, aiming to determine how countries can leverage international trade to enhance economic development.

Turing Events